A Nature-Inspired Experimental Method for Re-Generating Porous Architectural Systems Based on Environmentally Data-Driven Performance Article Swipe
C. H. Li
,
Ding Wen Bao
,
Xin Yan
,
Renhu Wu
,
Chenming He
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.52842/conf.caadria.2023.1.271
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.52842/conf.caadria.2023.1.271
Weathering scenery, as one of the most representative time-consuming natural features, is associated with many characteristics through aspects of specialized morphology, porosity, adaptability, and regenerative ability.Because of its unique porous structure and majestic, randomly three-dimensional composition, it has inspired lots of creations in industrial design, art crafts, and graphic design fields.But in architectural generative design, very limited projects are related to weathering.However, in recent decades, the advancements in computer-aided design tools have made it possible to implement rigorous computational methods in complex geometrical systems.This research tries to learn from the weathering evolution and apply the characteristics in the pursuit of enriching nature-inspired architecture.The experiments will focus on one specific weathering behavior, using wind-blown particles as weathering agents, and introduce an experimental method of generating the performance-based porosity architectural system responding to environmental agents' effects.Computational Fluid Dynamics (CFD), Bi-Directional Evolutionary Structural Optimization (BESO), and Swarm Intelligence are employed to negotiate between surface, structure, and environmental space.This study of the porosity architectural system is concerned not only with discovering new possibilities for intricate and complex nature-inspired architectural forms, but also with negotiating and considering humans and nature as equal decision-makers.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.52842/conf.caadria.2023.1.271
- http://papers.cumincad.org/data/works/att/caadria2023_246.pdf
- OA Status
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- References
- 12
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- OpenAlex ID
- https://openalex.org/W4380761049
All OpenAlex metadata
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https://openalex.org/W4380761049Canonical identifier for this work in OpenAlex
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https://doi.org/10.52842/conf.caadria.2023.1.271Digital Object Identifier
- Title
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A Nature-Inspired Experimental Method for Re-Generating Porous Architectural Systems Based on Environmentally Data-Driven PerformanceWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
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C. H. Li, Ding Wen Bao, Xin Yan, Renhu Wu, Chenming HeList of authors in order
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https://doi.org/10.52842/conf.caadria.2023.1.271Publisher landing page
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https://papers.cumincad.org/data/works/att/caadria2023_246.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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-
bronzeOpen access status per OpenAlex
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https://papers.cumincad.org/data/works/att/caadria2023_246.pdfDirect OA link when available
- Concepts
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Computer science, Porosity, Engineering, Geotechnical engineeringTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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12Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| citation_normalized_percentile.value | 0.13846154 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |